Comparing the Halogen Bond to the Hydrogen Bond by Solid‐State NMR Spectroscopy: Anion Coordinated Dimers from 2‐ and 3‐Iodoethynylpyridine Salts
Bibliographic record
Abstract
Abstract Halogen bonding is an increasingly important tool in crystal engineering, and measuring its influence on the local chemical and electronic environment is necessary to fully understand this interaction. Here, we present a systematic crystallographic and solid‐state NMR study of self‐complementary halogen‐bonded frameworks built from the halide salts (HCl, HBr, HI, HI3) of 2‐iodoethynylpyridine and 3‐iodoethynylpyridine. A series of single crystal X‐ray structures reveals the formation of discrete charged dimers in the solid state, directed by simultaneous X−⋅⋅⋅H−N+ hydrogen bonds and C−I⋅⋅⋅X− halogen bonds (X=Cl, Br, I). Each compound was studied using multinuclear solid‐state magnetic resonance spectroscopy, observing 1H to investigate the hydrogen bonds and 13C, 35Cl, and 79/81Br to investigate the halogen bonds. A natural localized molecular orbital analysis was employed to help interpret the experimental results. 1H SSNMR spectroscopy reveals a decrease in the chemical shift of the proton participating in the hydrogen bond as the halogen increases in size, whereas the 13C SSNMR reveals an increased 13C chemical shift of the C−I carbon for C−I⋅⋅⋅X− relative to C−I⋅⋅⋅N halogen bonds. Additionally, 35Cl and 79/81Br SSNMR, along with computational results, have allowed us to compare the C−I⋅⋅⋅X− halogen bond involving each halide in terms of NMR observables. Due to the isostructural nature of these compounds, they are ideal cases for experimentally assessing the impact of different halogen bond acceptors on the solid‐state NMR response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".